-- =============================================================================
-- Migration: 014_primitive_classification_system.sql
-- Purpose: Create primitive classification system for context-aware review analysis
-- =============================================================================
--
-- This migration introduces a "primitive" classification system that allows
-- industry-specific and category-specific configuration of what aspects to
-- look for when classifying reviews.
--
-- Components:
--   1. pipeline.primitives - Frozen dictionary of primitives (quality dimensions)
--   2. ALTER public.gbp_categories - Add primitive_configs and business_context
--   3. pipeline.jsonb_deep_merge() - Recursive JSONB merge function
--   4. pipeline.resolve_primitive_config() - Resolve configs through category tree
--   5. pipeline.get_classification_context() - Get full classification context
--
-- Date: 2026-01-31
-- =============================================================================


-- =============================================================================
-- SECTION 1: PRIMITIVES TABLE (Frozen Dictionary)
-- =============================================================================

CREATE TABLE IF NOT EXISTS pipeline.primitives (
    code VARCHAR(30) PRIMARY KEY,
    dimension VARCHAR(20) NOT NULL,  -- quality, service, process, environment, value, trust, resolution, loyalty, escape
    name VARCHAR(100) NOT NULL,
    definition TEXT NOT NULL,
    is_meta BOOLEAN DEFAULT FALSE,  -- true for always-active primitives (HONESTY, ETHICS, etc.)
    base_positive_signals TEXT[],
    base_negative_signals TEXT[],
    created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
);

-- Index on dimension for filtering
CREATE INDEX IF NOT EXISTS idx_primitives_dimension ON pipeline.primitives(dimension);

-- Index on is_meta for quick access to always-active primitives
CREATE INDEX IF NOT EXISTS idx_primitives_is_meta ON pipeline.primitives(is_meta) WHERE is_meta = TRUE;

COMMENT ON TABLE pipeline.primitives IS 'Frozen dictionary of classification primitives (quality dimensions)';
COMMENT ON COLUMN pipeline.primitives.code IS 'Unique identifier for the primitive (e.g., FOOD_TASTE, SERVICE_SPEED)';
COMMENT ON COLUMN pipeline.primitives.dimension IS 'Category of the primitive (quality, service, process, etc.)';
COMMENT ON COLUMN pipeline.primitives.is_meta IS 'If true, this primitive is always active regardless of category config';
COMMENT ON COLUMN pipeline.primitives.base_positive_signals IS 'Default positive signal keywords for this primitive';
COMMENT ON COLUMN pipeline.primitives.base_negative_signals IS 'Default negative signal keywords for this primitive';


-- =============================================================================
-- SECTION 2: ALTER gbp_categories TABLE
-- =============================================================================

-- Add primitive_configs column (JSONB for flexible config)
ALTER TABLE public.gbp_categories
ADD COLUMN IF NOT EXISTS primitive_configs JSONB DEFAULT '{}';

-- Add business_context column (JSONB for industry-specific context)
ALTER TABLE public.gbp_categories
ADD COLUMN IF NOT EXISTS business_context JSONB DEFAULT '{}';

-- Add config versioning columns
ALTER TABLE public.gbp_categories
ADD COLUMN IF NOT EXISTS config_version VARCHAR(20);

ALTER TABLE public.gbp_categories
ADD COLUMN IF NOT EXISTS config_generated_by VARCHAR(100);

ALTER TABLE public.gbp_categories
ADD COLUMN IF NOT EXISTS config_updated_at TIMESTAMP WITH TIME ZONE;

-- GIN indexes for JSONB containment queries
CREATE INDEX IF NOT EXISTS idx_gbp_categories_primitive_configs
ON public.gbp_categories USING GIN (primitive_configs);

CREATE INDEX IF NOT EXISTS idx_gbp_categories_business_context
ON public.gbp_categories USING GIN (business_context);

-- Index for config version lookups
CREATE INDEX IF NOT EXISTS idx_gbp_categories_config_version
ON public.gbp_categories(config_version) WHERE config_version IS NOT NULL;

COMMENT ON COLUMN public.gbp_categories.primitive_configs IS 'JSONB config for primitives at this category level (inherits from ancestors)';
COMMENT ON COLUMN public.gbp_categories.business_context IS 'JSONB business context for this category (industry-specific terminology, etc.)';
COMMENT ON COLUMN public.gbp_categories.config_version IS 'Version of the primitive config (for cache invalidation)';
COMMENT ON COLUMN public.gbp_categories.config_generated_by IS 'Tool/model that generated this config';
COMMENT ON COLUMN public.gbp_categories.config_updated_at IS 'When the config was last updated';


-- =============================================================================
-- SECTION 3: JSONB DEEP MERGE FUNCTION
-- =============================================================================

-- Recursive JSONB merge function
-- - Objects: recursively merge (override wins on conflicts)
-- - Arrays: union with dedup by default
-- - If object has "__replace__": true, replace entirely instead of merge
CREATE OR REPLACE FUNCTION pipeline.jsonb_deep_merge(
    base JSONB,
    override JSONB
) RETURNS JSONB AS $$
DECLARE
    result JSONB;
    key TEXT;
    base_value JSONB;
    override_value JSONB;
    merged_array JSONB;
BEGIN
    -- Handle NULL cases
    IF base IS NULL THEN
        RETURN override;
    END IF;

    IF override IS NULL THEN
        RETURN base;
    END IF;

    -- If override has __replace__ flag, return override without the flag
    IF jsonb_typeof(override) = 'object' AND override ? '__replace__' AND (override->>'__replace__')::boolean = true THEN
        RETURN override - '__replace__';
    END IF;

    -- If both are not objects, override wins
    IF jsonb_typeof(base) != 'object' OR jsonb_typeof(override) != 'object' THEN
        RETURN override;
    END IF;

    -- Both are objects, merge recursively
    result := base;

    FOR key IN SELECT jsonb_object_keys(override)
    LOOP
        override_value := override->key;

        IF NOT (base ? key) THEN
            -- Key doesn't exist in base, just add it
            result := result || jsonb_build_object(key, override_value);
        ELSE
            base_value := base->key;

            -- Check for __replace__ flag in the override value
            IF jsonb_typeof(override_value) = 'object'
               AND override_value ? '__replace__'
               AND (override_value->>'__replace__')::boolean = true THEN
                -- Replace entirely (without the __replace__ flag)
                result := result || jsonb_build_object(key, override_value - '__replace__');

            -- If both are objects, recurse
            ELSIF jsonb_typeof(base_value) = 'object' AND jsonb_typeof(override_value) = 'object' THEN
                result := result || jsonb_build_object(
                    key,
                    pipeline.jsonb_deep_merge(base_value, override_value)
                );

            -- If both are arrays, union with dedup
            ELSIF jsonb_typeof(base_value) = 'array' AND jsonb_typeof(override_value) = 'array' THEN
                -- Union arrays, remove duplicates
                -- Using a subquery to deduplicate
                SELECT jsonb_agg(DISTINCT elem)
                INTO merged_array
                FROM (
                    SELECT jsonb_array_elements(base_value) AS elem
                    UNION
                    SELECT jsonb_array_elements(override_value) AS elem
                ) AS combined;

                result := result || jsonb_build_object(key, COALESCE(merged_array, '[]'::jsonb));

            -- Otherwise, override wins
            ELSE
                result := result || jsonb_build_object(key, override_value);
            END IF;
        END IF;
    END LOOP;

    RETURN result;
END;
$$ LANGUAGE plpgsql IMMUTABLE;

COMMENT ON FUNCTION pipeline.jsonb_deep_merge(JSONB, JSONB) IS
'Recursively merges two JSONB objects. Objects are merged recursively (override wins on conflicts).
Arrays are unioned with dedup. Use {"__replace__": true, ...} to replace instead of merge.';


-- =============================================================================
-- SECTION 4: RESOLVE PRIMITIVE CONFIG FUNCTION
-- =============================================================================

-- Resolves primitive config by merging ancestor configs (general -> specific)
CREATE OR REPLACE FUNCTION pipeline.resolve_primitive_config(
    p_path ltree
) RETURNS JSONB AS $$
DECLARE
    result JSONB := '{}';
    row_config JSONB;
BEGIN
    -- Fetch all ancestor nodes (including self), ordered by level ASC (general -> specific)
    -- Uses @> operator: p_path is a descendant of (or equal to) the node's path
    FOR row_config IN
        SELECT primitive_configs
        FROM public.gbp_categories
        WHERE p_path <@ path  -- p_path is descendant of or equal to path
        ORDER BY level ASC
    LOOP
        -- Skip NULL or empty configs
        IF row_config IS NOT NULL AND row_config != '{}' THEN
            result := pipeline.jsonb_deep_merge(result, row_config);
        END IF;
    END LOOP;

    RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;

COMMENT ON FUNCTION pipeline.resolve_primitive_config(ltree) IS
'Resolves the full primitive config for a category path by merging all ancestor configs from general to specific.';


-- =============================================================================
-- SECTION 5: RESOLVE BUSINESS CONTEXT FUNCTION
-- =============================================================================

-- Resolves business context by merging ancestor contexts (general -> specific)
CREATE OR REPLACE FUNCTION pipeline.resolve_business_context(
    p_path ltree
) RETURNS JSONB AS $$
DECLARE
    result JSONB := '{}';
    row_context JSONB;
BEGIN
    -- Fetch all ancestor nodes (including self), ordered by level ASC (general -> specific)
    FOR row_context IN
        SELECT business_context
        FROM public.gbp_categories
        WHERE p_path <@ path
        ORDER BY level ASC
    LOOP
        -- Skip NULL or empty contexts
        IF row_context IS NOT NULL AND row_context != '{}' THEN
            result := pipeline.jsonb_deep_merge(result, row_context);
        END IF;
    END LOOP;

    RETURN result;
END;
$$ LANGUAGE plpgsql STABLE;

COMMENT ON FUNCTION pipeline.resolve_business_context(ltree) IS
'Resolves the full business context for a category path by merging all ancestor contexts from general to specific.';


-- =============================================================================
-- SECTION 6: GET CLASSIFICATION CONTEXT FUNCTION
-- =============================================================================

-- Returns complete classification context for a category path
CREATE OR REPLACE FUNCTION pipeline.get_classification_context(
    p_path ltree
) RETURNS JSONB AS $$
DECLARE
    resolved_primitives JSONB;
    resolved_context JSONB;
    primitives_dict JSONB;
BEGIN
    -- Resolve the primitive config for this path
    resolved_primitives := pipeline.resolve_primitive_config(p_path);

    -- Resolve the business context for this path
    resolved_context := pipeline.resolve_business_context(p_path);

    -- Build the primitives dictionary from the primitives table
    SELECT jsonb_object_agg(
        code,
        jsonb_build_object(
            'code', code,
            'dimension', dimension,
            'name', name,
            'definition', definition,
            'is_meta', is_meta,
            'base_positive_signals', COALESCE(to_jsonb(base_positive_signals), '[]'::jsonb),
            'base_negative_signals', COALESCE(to_jsonb(base_negative_signals), '[]'::jsonb)
        )
    )
    INTO primitives_dict
    FROM pipeline.primitives;

    -- Handle case where primitives table is empty
    IF primitives_dict IS NULL THEN
        primitives_dict := '{}'::jsonb;
    END IF;

    -- Return combined context object
    RETURN jsonb_build_object(
        'primitive_configs', resolved_primitives,
        'business_context', resolved_context,
        'primitives_dictionary', primitives_dict,
        'category_path', p_path::text,
        'resolved_at', NOW()
    );
END;
$$ LANGUAGE plpgsql STABLE;

COMMENT ON FUNCTION pipeline.get_classification_context(ltree) IS
'Returns complete classification context for a category path, including resolved primitive configs,
business context, and the full primitives dictionary.';


-- =============================================================================
-- SECTION 7: HELPER FUNCTION - GET ACTIVE PRIMITIVES
-- =============================================================================

-- Returns the list of active primitive codes for a category path
-- (includes meta primitives + enabled primitives from config)
CREATE OR REPLACE FUNCTION pipeline.get_active_primitives(
    p_path ltree
) RETURNS TEXT[] AS $$
DECLARE
    resolved_config JSONB;
    active_codes TEXT[];
    meta_codes TEXT[];
    config_enabled TEXT[];
    config_disabled TEXT[];
BEGIN
    -- Get resolved config
    resolved_config := pipeline.resolve_primitive_config(p_path);

    -- Get all meta primitives (always active)
    SELECT array_agg(code)
    INTO meta_codes
    FROM pipeline.primitives
    WHERE is_meta = TRUE;

    -- Get enabled primitives from config
    IF resolved_config ? 'enabled' THEN
        SELECT array_agg(elem::text)
        INTO config_enabled
        FROM jsonb_array_elements_text(resolved_config->'enabled') AS elem;
    END IF;

    -- Get disabled primitives from config
    IF resolved_config ? 'disabled' THEN
        SELECT array_agg(elem::text)
        INTO config_disabled
        FROM jsonb_array_elements_text(resolved_config->'disabled') AS elem;
    END IF;

    -- Combine: meta + enabled, minus disabled
    active_codes := COALESCE(meta_codes, ARRAY[]::TEXT[]) || COALESCE(config_enabled, ARRAY[]::TEXT[]);

    -- Remove disabled primitives
    IF config_disabled IS NOT NULL THEN
        active_codes := array(
            SELECT unnest(active_codes)
            EXCEPT
            SELECT unnest(config_disabled)
        );
    END IF;

    -- Remove duplicates
    active_codes := array(SELECT DISTINCT unnest(active_codes));

    RETURN active_codes;
END;
$$ LANGUAGE plpgsql STABLE;

COMMENT ON FUNCTION pipeline.get_active_primitives(ltree) IS
'Returns array of active primitive codes for a category path (meta primitives + enabled - disabled).';


-- =============================================================================
-- SECTION 8: SEED INITIAL PRIMITIVES (Examples)
-- =============================================================================

-- Insert some example primitives (can be extended later)
INSERT INTO pipeline.primitives (code, dimension, name, definition, is_meta, base_positive_signals, base_negative_signals)
VALUES
    -- Meta primitives (always active)
    ('HONESTY', 'trust', 'Honesty & Truthfulness', 'Whether the business is perceived as honest and truthful in their dealings', TRUE,
     ARRAY['honest', 'truthful', 'transparent', 'upfront', 'no hidden'],
     ARRAY['lied', 'dishonest', 'deceptive', 'misleading', 'hidden fees', 'bait and switch']),

    ('ETHICS', 'trust', 'Ethical Behavior', 'Whether the business behaves ethically and with integrity', TRUE,
     ARRAY['ethical', 'integrity', 'fair', 'principled', 'moral'],
     ARRAY['unethical', 'scam', 'fraud', 'cheat', 'ripoff', 'shady']),

    ('SAFETY', 'trust', 'Safety & Security', 'Whether customers feel safe and secure', TRUE,
     ARRAY['safe', 'secure', 'protected', 'trust'],
     ARRAY['unsafe', 'dangerous', 'security concern', 'risk', 'hazard']),

    -- Quality dimension primitives
    ('FOOD_TASTE', 'quality', 'Food Taste & Flavor', 'Quality and taste of food items', FALSE,
     ARRAY['delicious', 'tasty', 'flavorful', 'yummy', 'amazing taste', 'perfectly seasoned'],
     ARRAY['bland', 'tasteless', 'bad taste', 'over-seasoned', 'under-seasoned', 'disgusting']),

    ('FOOD_FRESHNESS', 'quality', 'Food Freshness', 'Freshness of ingredients and food items', FALSE,
     ARRAY['fresh', 'crisp', 'just made', 'homemade', 'organic'],
     ARRAY['stale', 'old', 'not fresh', 'frozen', 'reheated', 'expired']),

    ('FOOD_PORTION', 'quality', 'Portion Size', 'Size and quantity of food servings', FALSE,
     ARRAY['generous portions', 'large serving', 'filling', 'plenty of food'],
     ARRAY['small portions', 'tiny', 'not enough', 'skimpy', 'overpriced for size']),

    ('PRODUCT_QUALITY', 'quality', 'Product Quality', 'Overall quality of products', FALSE,
     ARRAY['high quality', 'well made', 'premium', 'durable', 'excellent quality'],
     ARRAY['poor quality', 'cheap', 'flimsy', 'broke easily', 'defective']),

    -- Service dimension primitives
    ('SERVICE_SPEED', 'service', 'Service Speed', 'Speed and timeliness of service', FALSE,
     ARRAY['fast', 'quick', 'prompt', 'efficient', 'no wait'],
     ARRAY['slow', 'long wait', 'took forever', 'delayed', 'waited too long']),

    ('SERVICE_FRIENDLINESS', 'service', 'Staff Friendliness', 'Friendliness and warmth of staff', FALSE,
     ARRAY['friendly', 'welcoming', 'warm', 'nice', 'pleasant', 'smiled'],
     ARRAY['rude', 'unfriendly', 'cold', 'dismissive', 'attitude', 'ignored']),

    ('SERVICE_KNOWLEDGE', 'service', 'Staff Knowledge', 'Knowledge and expertise of staff', FALSE,
     ARRAY['knowledgeable', 'expert', 'helpful advice', 'knew their stuff', 'professional'],
     ARRAY['clueless', 'didnt know', 'unhelpful', 'inexperienced', 'untrained']),

    ('SERVICE_ATTENTIVENESS', 'service', 'Staff Attentiveness', 'How attentive staff are to customer needs', FALSE,
     ARRAY['attentive', 'checked on us', 'responsive', 'available', 'proactive'],
     ARRAY['inattentive', 'ignored', 'couldnt find anyone', 'had to flag down', 'neglected']),

    -- Environment dimension primitives
    ('ENV_CLEANLINESS', 'environment', 'Cleanliness', 'Cleanliness of the establishment', FALSE,
     ARRAY['clean', 'spotless', 'tidy', 'well-maintained', 'hygienic'],
     ARRAY['dirty', 'filthy', 'messy', 'gross', 'sticky', 'unhygienic']),

    ('ENV_AMBIANCE', 'environment', 'Ambiance & Atmosphere', 'Overall atmosphere and vibe', FALSE,
     ARRAY['great atmosphere', 'nice ambiance', 'cozy', 'relaxing', 'beautiful decor'],
     ARRAY['bad atmosphere', 'uncomfortable', 'loud', 'cramped', 'depressing']),

    ('ENV_PARKING', 'environment', 'Parking Availability', 'Availability and convenience of parking', FALSE,
     ARRAY['easy parking', 'plenty of parking', 'free parking', 'valet available'],
     ARRAY['no parking', 'hard to park', 'paid parking', 'had to park far']),

    -- Value dimension primitives
    ('VALUE_PRICE', 'value', 'Price Level', 'Perception of price levels', FALSE,
     ARRAY['affordable', 'reasonable prices', 'cheap', 'good deal', 'budget-friendly'],
     ARRAY['expensive', 'overpriced', 'pricey', 'not worth the price', 'too costly']),

    ('VALUE_WORTH', 'value', 'Value for Money', 'Whether the experience is worth the cost', FALSE,
     ARRAY['worth it', 'great value', 'bang for buck', 'money well spent'],
     ARRAY['not worth it', 'waste of money', 'rip off', 'should be cheaper']),

    -- Process dimension primitives
    ('PROCESS_BOOKING', 'process', 'Booking & Reservations', 'Ease of making reservations or appointments', FALSE,
     ARRAY['easy to book', 'simple reservation', 'available appointments', 'online booking'],
     ARRAY['hard to book', 'no availability', 'complicated booking', 'had to call multiple times']),

    ('PROCESS_WAIT', 'process', 'Wait Times', 'Time spent waiting for service', FALSE,
     ARRAY['no wait', 'seated immediately', 'quick turnaround'],
     ARRAY['long wait', 'waited forever', 'always busy', 'need to wait in line']),

    -- Resolution dimension primitives
    ('RESOLUTION_RESPONSE', 'resolution', 'Problem Response', 'How problems and complaints are handled', FALSE,
     ARRAY['fixed the issue', 'made it right', 'apologized', 'took responsibility'],
     ARRAY['ignored complaint', 'didnt care', 'blamed me', 'no resolution', 'refused to help']),

    -- Loyalty dimension primitives
    ('LOYALTY_RETURN', 'loyalty', 'Return Intent', 'Whether customers intend to return', FALSE,
     ARRAY['will be back', 'coming back', 'regular customer', 'my go-to place'],
     ARRAY['never again', 'wont return', 'last time', 'not coming back']),

    ('LOYALTY_RECOMMEND', 'loyalty', 'Recommendation Intent', 'Whether customers would recommend to others', FALSE,
     ARRAY['highly recommend', 'tell everyone', 'bring friends', 'must try'],
     ARRAY['dont recommend', 'avoid', 'stay away', 'warned friends']),

    -- Escape dimension primitives (when customers leave early or avoid)
    ('ESCAPE_LEFT', 'escape', 'Early Departure', 'Whether customers left early or walked out', FALSE,
     ARRAY[]::TEXT[],  -- No positive signals for escape
     ARRAY['walked out', 'left early', 'didnt finish', 'had to leave', 'couldnt stay'])

ON CONFLICT (code) DO UPDATE SET
    dimension = EXCLUDED.dimension,
    name = EXCLUDED.name,
    definition = EXCLUDED.definition,
    is_meta = EXCLUDED.is_meta,
    base_positive_signals = EXCLUDED.base_positive_signals,
    base_negative_signals = EXCLUDED.base_negative_signals;


-- =============================================================================
-- SECTION 9: EXAMPLE CATEGORY CONFIGS
-- =============================================================================

-- Example: Set primitive config for Food & Dining sector (level 1)
-- This would enable food-related primitives for all food businesses
UPDATE public.gbp_categories
SET
    primitive_configs = '{
        "enabled": ["FOOD_TASTE", "FOOD_FRESHNESS", "FOOD_PORTION", "SERVICE_SPEED", "SERVICE_FRIENDLINESS", "ENV_CLEANLINESS", "ENV_AMBIANCE", "VALUE_PRICE", "VALUE_WORTH", "PROCESS_WAIT"],
        "weights": {
            "FOOD_TASTE": 1.5,
            "FOOD_FRESHNESS": 1.3,
            "SERVICE_SPEED": 1.2
        }
    }'::jsonb,
    business_context = '{
        "terminology": {
            "staff": ["server", "waiter", "waitress", "host", "hostess", "bartender"],
            "product": ["food", "dish", "meal", "appetizer", "entree", "dessert", "drink"]
        },
        "industry": "food_service"
    }'::jsonb,
    config_version = 'v1.0.0',
    config_generated_by = 'migration_014',
    config_updated_at = NOW()
WHERE slug = 'food_dining' AND level = 1;

-- Example: Override config for Restaurants (level 2) - adds more specific settings
UPDATE public.gbp_categories
SET
    primitive_configs = '{
        "enabled": ["PROCESS_BOOKING", "ENV_PARKING"],
        "weights": {
            "PROCESS_WAIT": 1.3
        },
        "signals": {
            "FOOD_TASTE": {
                "positive": ["perfectly cooked", "chef special", "signature dish"],
                "negative": ["undercooked", "overcooked", "cold food"]
            }
        }
    }'::jsonb,
    business_context = '{
        "terminology": {
            "staff": ["chef", "cook", "sous chef", "kitchen staff"]
        },
        "typical_visit_duration": "1-2 hours",
        "reservation_common": true
    }'::jsonb,
    config_version = 'v1.0.0',
    config_generated_by = 'migration_014',
    config_updated_at = NOW()
WHERE slug = 'restaurants' AND level = 2;


-- =============================================================================
-- VERIFICATION QUERIES (can be removed in production)
-- =============================================================================

-- Verify primitives table
DO $$
BEGIN
    RAISE NOTICE 'Primitives table created with % rows', (SELECT COUNT(*) FROM pipeline.primitives);
END $$;

-- Verify functions exist
DO $$
BEGIN
    -- Test jsonb_deep_merge
    ASSERT pipeline.jsonb_deep_merge('{"a": 1}'::jsonb, '{"b": 2}'::jsonb) = '{"a": 1, "b": 2}'::jsonb,
        'jsonb_deep_merge basic test failed';

    -- Test __replace__ flag
    ASSERT pipeline.jsonb_deep_merge('{"a": {"x": 1, "y": 2}}'::jsonb, '{"a": {"__replace__": true, "z": 3}}'::jsonb) = '{"a": {"z": 3}}'::jsonb,
        'jsonb_deep_merge __replace__ test failed';

    RAISE NOTICE 'All function tests passed';
END $$;